Biomedical Signal Analysis for Connected Healthcare

Biomedical Signal Analysis for Connected Healthcare

Author: Sridhar Krishnan

Publisher: Elsevier

ISBN: 9780128130865

Category: Technology & Engineering

Page: 334

View: 634

Biomedical Signal Analysis for Connected Healthcare provides rigorous coverage on several generations of techniques, including time domain approaches for event detection, spectral analysis for interpretation of clinical events of interest, time-varying signal processing for understanding dynamical aspects of complex biomedical systems, the application of machine learning principles in enhanced clinical decision-making, the application of sparse techniques and compressive sensing in providing low-power applications that are essential for wearable designs, the emerging paradigms of the Internet of Things, and connected healthcare. Provides comprehensive coverage of biomedical engineering, technologies, and healthcare applications of various physiological signals Covers vital signals, including ECG, EEG, EMG and body sounds Includes case studies and MATLAB code for selected applications

Biomedical Signal Analysis for Connected Healthcare

Biomedical Signal Analysis for Connected Healthcare

Author: Sridhar Krishnan

Publisher: Academic Press

ISBN: 9780128131732

Category: Technology & Engineering

Page: 334

View: 303

Biomedical Signal Analysis for Connected Healthcare provides rigorous coverage on several generations of techniques, including time domain approaches for event detection, spectral analysis for interpretation of clinical events of interest, time-varying signal processing for understanding dynamical aspects of complex biomedical systems, the application of machine learning principles in enhanced clinical decision-making, the application of sparse techniques and compressive sensing in providing low-power applications that are essential for wearable designs, the emerging paradigms of the Internet of Things, and connected healthcare. Provides comprehensive coverage of biomedical engineering, technologies, and healthcare applications of various physiological signals Covers vital signals, including ECG, EEG, EMG and body sounds Includes case studies and MATLAB code for selected applications

Biomedical Signal Processing for Healthcare Applications

Biomedical Signal Processing for Healthcare Applications

Author: Varun Bajaj

Publisher: CRC Press

ISBN: 9781000413304

Category: Technology & Engineering

Page: 336

View: 776

This book examines the use of biomedical signal processing—EEG, EMG, and ECG—in analyzing and diagnosing various medical conditions, particularly diseases related to the heart and brain. In combination with machine learning tools and other optimization methods, the analysis of biomedical signals greatly benefits the healthcare sector by improving patient outcomes through early, reliable detection. The discussion of these modalities promotes better understanding, analysis, and application of biomedical signal processing for specific diseases. The major highlights of Biomedical Signal Processing for Healthcare Applications include biomedical signals, acquisition of signals, pre-processing and analysis, post-processing and classification of the signals, and application of analysis and classification for the diagnosis of brain- and heart-related diseases. Emphasis is given to brain and heart signals because incomplete interpretations are made by physicians of these aspects in several situations, and these partial interpretations lead to major complications. FEATURES Examines modeling and acquisition of biomedical signals of different disorders Discusses CAD-based analysis of diagnosis useful for healthcare Includes all important modalities of biomedical signals, such as EEG, EMG, MEG, ECG, and PCG Includes case studies and research directions, including novel approaches used in advanced healthcare systems This book can be used by a wide range of users, including students, research scholars, faculty, and practitioners in the field of biomedical engineering and medical image analysis and diagnosis.

Digital Health Approach for Predictive, Preventive, Personalised and Participatory Medicine

Digital Health Approach for Predictive, Preventive, Personalised and Participatory Medicine

Author: Lotfi Chaari

Publisher: Springer

ISBN: 9783030118006

Category: Medical

Page: 88

View: 498

This collection, entitled Digital Health for Predictive, Preventive, Personalized and Participatory Medicine contains the proceedings of the first International conference on digital healthtechnologies (ICDHT 2018). Ten recent contributions in the fields of Artificial Intelligence (AI) and machine learning, Internet of Things (IoT) and data analysis, all applied to digital health. This collection enables researchers to learn about recent advances in the above mentioned fields. It brings a technological viewpoint of P4 medicine. Readers will discover how advanced Information Technology (IT) tools can be used for healthcare. For instance, the use of connected objects to monitor physiological parameters is discussed. Moreover, even if compressed sensing is nowadays a common acquisition technique, its use for IoT is presented in this collection through one of the pioneer works in the field. In addition, the use of AI for epileptic seizure detection is also discussed as being one of the major concerns of predictive medicine both in industrialized and low-income countries. This work is edited by Prof. Lotfi Chaari, professor at the University of Sfax, and previously at the University of Toulouse. This work comes after more than ten years of expertise in the biomedical signal and image processing field.

Machine Learning and the Internet of Medical Things in Healthcare

Machine Learning and the Internet of Medical Things in Healthcare

Author: Krishna Kant Singh

Publisher: Academic Press

ISBN: 9780128232170

Category: Science

Page: 290

View: 367

Machine Learning and the Internet of Medical Things in Healthcare discusses the applications and challenges of machine learning for healthcare applications. The book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers worldwide. The book includes deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. It also presents the concepts of the Internet of Things, the set of technologies that develops traditional devices into smart devices. Finally, the book offers research perspectives, covering the convergence of machine learning and IoT. It also presents the application of these technologies in the development of healthcare frameworks. Provides an introduction to the Internet of Medical Things through the principles and applications of machine learning Explains the functions and applications of machine learning in various applications such as ultrasound imaging, biomedical signal processing, robotics, and biomechatronics Includes coverage of the evolution of healthcare applications with machine learning, including Clinical Decision Support Systems, artificial intelligence in biomedical engineering, and AI-enabled connected health informatics, supported by real-world case studies

Health Monitoring Systems

Health Monitoring Systems

Author: Rajarshi Gupta

Publisher: CRC Press

ISBN: 9780429532559

Category: Medical

Page: 320

View: 633

Remote health monitoring using wearable sensors is an important research area involving several key steps: physiological parameter sensing and data acquisition, data analysis, data security, data transmission to caregivers, and clinical intervention, all of which play a significant role to form a closed loop system. Subject-specific behavioral and clinical traits, coupled with individual physiological differences, necessitate a personalized healthcare delivery model for around-the-clock monitoring within the home environment. Cardiovascular disease monitoring is an illustrative application domain where research has been instrumental in enabling a personalized closed-loop monitoring system, which has been showcased in this book. Health Monitoring Systems: An Enabling Technology for Patient Care provides a holistic overview of state-of-the-art monitoring systems facilitated by Internet of Things (IoT) technology. The book lists out the details on biomedical signal acquisition, processing, and data security, the fundamental building blocks towards an ambulatory health monitoring infrastructure. The fundamentals have been complimented with other relevant topics including applications which provide an in-depth view on remote health monitoring systems. Key Features: Presents examples of state-of-the-art health monitoring systems using IoT infrastructure Covers the full spectrum of physiological sensing, data acquisition, processing, and data security Provides relevant example applications demonstrating the benefits of technological advancements aiding disease prognosis This book serves as a beginner’s guide for engineering students of electrical and computer science, practicing engineers, researchers, and scientists who are interested in having an overview of pervasive health monitoring systems using body-worn sensors operating outside the hospital environment. It could also be recommended as a reference for a graduate or master’s level course on biomedical instrumentation and signal processing.

Emergent Converging Technologies and Biomedical Systems

Emergent Converging Technologies and Biomedical Systems

Author: N. Marriwala

Publisher: Springer Nature

ISBN: 9789811687747

Category: Technology & Engineering

Page: 742

View: 748

The book contains peer-reviewed proceedings of the International Conference on Emergent Converging Technologies and Biomedical Systems 2021. It includes papers on wireless multimedia networks, green wireless networks, electric vehicles, biomedical signal processing and instrumentation, wearable sensors for health care monitoring, biomedical imaging, & bio-materials, modeling and simulation in medicine biomedical and health informatics. The book will serve as a useful guide for educators, researchers, and developers working in the area of signal processing, imaging, computing, instrumentation, artificial intelligence, and their related applications. This book will also provide support and aid to the researchers involved in designing the latest advancements in healthcare technologies.

New Frontiers of Cardiovascular Screening using Unobtrusive Sensors, AI, and IoT

New Frontiers of Cardiovascular Screening using Unobtrusive Sensors, AI, and IoT

Author: Anirban Dutta Choudhury

Publisher: Academic Press

ISBN: 9780128245002

Category: Technology & Engineering

Page: 232

View: 865

New Frontiers of Cardiovascular Screening using Unobtrusive Sensors, AI, and IoT provides insights into real-world problems in cardiovascular disease screening that can be addressed via AI, IoT and wearable based sensing. Non-Communicable Diseases (NCD) are surpassing CDS and emerging as the foremost cause of death. Hence, early screening of CVDs using wearable and other similar sensors is an extremely important global problem to solve. The digital health field is constantly changing, and this book provides a review of recent technology developments, offering unique coverage of processing time series physiological sensor data. The authors have developed this book with graduate and post graduate students in mind, making sure they provide an accessible entry point into the field. This book is particularly useful for engineers and computer scientists who want to build technologies that work in real world scenarios as it provides a practitioner’s view/insights /tricks of the trade. Finally, this book helps researchers working on this important problem to quickly ramp up their knowledge and research to the state-of-the-art. Maps digital health technology to real diseases that are relevant to the medical community Supported with patient data and case studies Gives practitioners insights into the real-world implementation of signal conditioning, signal processing and machine learning

Digital Health in Focus of Predictive, Preventive and Personalised Medicine

Digital Health in Focus of Predictive, Preventive and Personalised Medicine

Author: Lotfi Chaari

Publisher: Springer Nature

ISBN: 9783030498153

Category: Medical

Page: 164

View: 205

The edition will cover proceedings of the second International conference on digital health Technologies (ICDHT 2019). The conference will address the topic of P4 medicine from the information technology point of view, and will be focused on the following topics: - Artificial Intelligence for health • Knowledge extraction • Decision-aid systems • Data analysis and risk prediction • Machine learning, deep learning - Health data processing • Data preprocessing, cleaning, management and mining • Computer-aided detection • Big data analysis, prediction and prevention • Cognitive algorithms for healthcare handling dynamic context management • Augmented reality, Motion detection and activity recognition - Devices, infrastructure and communication • Wearable & connected devices • Communication infrastructures, architectures and standards Blockchain for e-Health • Computing/storage infrastructures for e-Health • IoT devices & architectures for Smart Healthcare - Health information systems • Telemedicine, Teleservices • Computing/storage infrastructures for e-Health • Clinical Data Visualisation Standards - Security and privacy for e-health • Health data Analytics for Security and Privacy • E-health Software and Hardware Security • Embedded Security for e-health - Applications in P4 medicine

Artificial Intelligence-Based Brain-Computer Interface

Artificial Intelligence-Based Brain-Computer Interface

Author: Varun Bajaj

Publisher: Academic Press

ISBN: 9780323914123

Category: Science

Page: 392

View: 269

Artificial Intelligence-Based Brain Computer Interface provides concepts of AI for modelling of non-invasive modalities of medical signals such as EEG, MRI, and FMRI. These modalities and their AI-based analysis are employed in BCI and related applications. This can help to improve the healthcare system through detection, identification, predication, analysis and classification of disease, management of chronic conditions, and delivery of health services. Artificial Intelligence-Based Brain Computer Interface emphasizes the real challenges in non-invasive input due to the complex nature of the human brain and for a variety of applications for analysis, classification and identification of different mental states. Each chapter starts with a description of a non-invasive input example and the need and motivation of the associated AI methods, along with discussions to connect the technology through BCI. Major topics include different AI methods/techniques such as Deep Neural Networks and Machine Learning algorithms for different non-invasive modalities such as EEG, MRI, FMRI for improving the diagnosis and prognosis of numerous disorders of the nervous system, cardiovascular system, musculoskeletal system, respiratory system and various organs of the body. The book also covers applications of AI in management of chronic condition, databases and delivery of health services. Various brain image modalities are analyzed and capabilities of the human brain will be exploited in BCI applications and case studies. The book presents AI methods for solving real-world problems and challenges in BCI and healthcare systems with the help of appropriate case studies and research results. Provides readers with an understanding of the key applications of Artificial Intelligence to Brain-Computer Interface for acquisition and modelling of non-invasive biomedical signal and image modalities for various conditions and disorders Integrates recent advancements of Artificial Intelligence to the evaluation of large amounts of clinical data for early detection of disorders such as Epilepsy, Alcoholism, Sleep Apnea, motor-imagery tasks classification, and others Provides readers with illustrative examples of how Artificial Intelligence can be applied to Brain-Computer Interface, including a wide range of case studies in predicting and classification of neurological disorders

Biomedical Signal Processing

Biomedical Signal Processing

Author: Metin Akay

Publisher:

ISBN: UOM:39015032580485

Category: Biomedical Engineering

Page: 377

View: 386

Sophisticated techniques for signal processing are now available to the biomedical specialist! Written in an easy-to-read, straightforward style, Biomedical Signal Processing presents techniques to eliminate background noise, enhance signal detection, and analyze computer data, making results easy to comprehend and apply. In addition to examining techniques for electrical signal analysis, filtering, and transforms, the author supplies an extensive appendix with several computer programs that demonstrate techniques presented in the text.

Internet of Things for Healthcare Technologies

Internet of Things for Healthcare Technologies

Author: Chinmay Chakraborty

Publisher: Springer Nature

ISBN: 9789811541124

Category: Technology & Engineering

Page: 324

View: 889

This book focuses on recent advances in the Internet of Things (IoT) in biomedical and healthcare technologies, presenting theoretical, methodological, well-established, and validated empirical work in these fields. Artificial intelligence and IoT are set to revolutionize all industries, but perhaps none so much as health care. Both biomedicine and machine learning applications are capable of analyzing data stored in national health databases in order to identify potential health problems, complications and effective protocols, and a range of wearable devices for biomedical and healthcare applications far beyond tracking individuals’ steps each day has emerged. These prosthetic technologies have made significant strides in recent decades with the advances in materials and development. As a result, more flexible, more mobile chip-enabled prosthetics or other robotic devices are on the horizon. For example, IoT-enabled wireless ECG sensors that reduce healthcare cost, and lead to better quality of life for cardiac patients. This book focuses on three current trends that are likely to have a significant impact on future healthcare: Advanced Medical Imaging and Signal Processing; Biomedical Sensors; and Biotechnological and Healthcare Advances. It also presents new methods of evaluating medical data, and diagnosing diseases in order to improve general quality of life.